Lonely Individuals Process the World in Idiosyncratic Ways.

Loneliness is detrimental to well-being and is often accompanied by self-reported feelings of not being understood by other people. What contributes to such feelings in lonely people? We used functional MRI of 66 first-year university students to unobtrusively measure the relative alignment of people's mental processing of naturalistic stimuli and tested whether lonely people actually process the world in idiosyncratic ways. We found evidence for such idiosyncrasy: Lonely individuals' neural responses were dissimilar to those of their peers, particularly in regions of the default-mode network in which similar responses have been associated with shared perspectives and subjective understanding. These relationships persisted when we controlled for demographic similarities, objective social isolation, and individuals' friendships with each other. Our findings raise the possibility that being surrounded by people who see the world differently from oneself, even if one is friends with them, may be a risk factor for loneliness.

Similarity Among Friends Serves as a Social Prior: The Assumption That "Birds of a Feather Flock Together" Shapes Social Decisions and Relationship Beliefs.

Social interactions unfold within networks of relationships. How do beliefs about others' social ties shape-and how are they shaped by-expectations about how others will behave? Here, participants joined a fictive online game-playing community and interacted with its purported members, who varied in terms of their trustworthiness and apparent relationships with one another. Participants were less trusting of partners with untrustworthy friends, even after they consistently showed themselves to be trustworthy, and were less willing to engage with them in the future. To test whether people not only expect friends to behave similarly but also expect those who behave similarly to be friends, an incidental memory test was given. Participants were exceptionally likely to falsely remember similarly behaving partners as friends. Thus, people expect friendship to predict similar behavior and vice versa. These results suggest that knowledge of social networks and others' behavioral tendencies reciprocally interact to shape social thought and behavior.

Neural encoding of novel social networks: evidence that perceivers prioritize others' centrality.

Knowledge of someone's friendships can powerfully impact how one interacts with them. Previous research suggests that information about others' real-world social network positions-e.g. how well-connected they are (centrality), 'degrees of separation' (relative social distance)-is spontaneously encoded when encountering familiar individuals. However, many types of information covary with where someone sits in a social network. For instance, strangers' face-based trait impressions are associated with their social network centrality, and social distance and centrality are inherently intertwined with familiarity, interpersonal similarity and memories. To disentangle the encoding of the social network position from other social information, participants learned a novel social network in which the social network position was decoupled from other factors and then saw each person's image during functional magnetic resonance imaging scanning. Using representational similarity analysis, we found that social network centrality was robustly encoded in regions associated with visual attention and mentalizing. Thus, even when considering a social network in which one is not included and where centrality is unlinked from perceptual and experience-based features to which it is inextricably tied in naturalistic contexts, the brain encodes information about others' importance in that network, likely shaping future perceptions of and interactions with those individuals.

Shared understanding and social connection: Integrating approaches from social psychology, social network analysis, and neuroscience.

Meaningfully connecting with others is critical to the well-being of individuals. What phenomena contribute to and stem from social connection? In this paper, we integrate emerging work that uses neuroimaging and social network analysis with theories that explore the links between shared reality and social connection. We highlight recent work suggesting that the extent to which people have aligned mental processing and shared subjective construals to those around them-as shown by neural similarity-is associated with both objective and subjective social connection. On the other hand, idiosyncrasies are linked to difficulties with social connection. We conclude by suggesting how the links between shared understanding and social connection can be productively used as a framework to study psychosocial phenomena of interest.

White matter connectivity in brain networks supporting social and affective processing predicts real-world social network characteristics.

Human behavior is embedded in social networks. Certain characteristics of the positions that people occupy within these networks appear to be stable within individuals. Such traits likely stem in part from individual differences in how people tend to think and behave, which may be driven by individual differences in the neuroanatomy supporting socio-affective processing. To investigate this possibility, we reconstructed the full social networks of three graduate student cohorts (N = 275; N = 279; N = 285), a subset of whom (N = 112) underwent diffusion magnetic resonance imaging. Although no single tract in isolation appears to be necessary or sufficient to predict social network characteristics, distributed patterns of white matter microstructural integrity in brain networks supporting social and affective processing predict eigenvector centrality (how well-connected someone is to well-connected others) and brokerage (how much one connects otherwise unconnected others). Thus, where individuals sit in their real-world social networks is reflected in their structural brain networks. More broadly, these results suggest that the application of data-driven methods to neuroimaging data can be a promising approach to investigate how brains shape and are shaped by individuals' positions in their real-world social networks.

Personality similarity predicts synchronous neural responses in fMRI and EEG data.

Successful communication and cooperation among different members of society depends, in part, on a consistent understanding of the physical and social world. What drives this alignment in perspectives? We present evidence from two neuroimaging studies using functional magnetic resonance imaging (fMRI; N = 66 with 2145 dyadic comparisons) and electroencephalography (EEG; N = 225 with 25,200 dyadic comparisons) to show that: (1) the extent to which people's neural responses are synchronized when viewing naturalistic stimuli is related to their personality profiles, and (2) that this effect is stronger than that of similarity in gender, ethnicity and political affiliation. The localization of the fMRI results in combination with the additional eye tracking analyses suggest that the relationship between personality similarity and neural synchrony likely reflects alignment in the interpretation of stimuli and not alignment in overt visual attention. Together, the findings suggest that similarity in psychological dispositions aligns people's reality via shared interpretations of the external world.

In-degree centrality in a social network is linked to coordinated neural activity.

Convergent processing of the world may be a factor that contributes to social connectedness. We use neuroimaging and network analysis to investigate the association between the social-network position (as measured by in-degree centrality) of first-year university students and their neural similarity while watching naturalistic audio-visual stimuli (specifically, videos). There were 119 students in the social-network study; 63 of them participated in the neuroimaging study. We show that more central individuals had similar neural responses to their peers and to each other in brain regions that are associated with high-level interpretations and social cognition (e.g., in the default mode network), whereas less-central individuals exhibited more variable responses. Self-reported enjoyment of and interest in stimuli followed a similar pattern, but accounting for these data did not change our main results. These findings show that neural processing of external stimuli is similar in highly-central individuals but is idiosyncratic in less-central individuals.

Mapping the social landscape: tracking patterns of interpersonal relationships.

It is widely believed that the demands of living in large, complexly bonded social groups played a key role in the evolution of human cognition. This review focuses on a critical but understudied skillset in the social-living toolkit: the ability to acquire, maintain, and use knowledge of the interpersonal relationships among the people around oneself. We provide a multidisciplinary synthesis of a diverse set of relevant findings, including recent work on the neural encoding and cognitive and behavioral consequences of knowledge of real-world social networks, research on how third-party relationship knowledge is tracked and used by children and other highly social primates, and research examining how people's knowledge of their social networks can be leveraged to inform the design of interventions aiming to promote behavior change or to efficiently spread information. We also highlight important unanswered questions and avenues in need of further exploration.

Psychological Science in the Wake of COVID-19: Social, Methodological, and Metascientific Considerations.

The COVID-19 pandemic has extensively changed the state of psychological science from what research questions psychologists can ask to which methodologies psychologists can use to investigate them. In this article, we offer a perspective on how to optimize new research in the pandemic's wake. Because this pandemic is inherently a social phenomenon-an event that hinges on human-to-human contact-we focus on socially relevant subfields of psychology. We highlight specific psychological phenomena that have likely shifted as a result of the pandemic and discuss theoretical, methodological, and practical considerations of conducting research on these phenomena. After this discussion, we evaluate metascientific issues that have been amplified by the pandemic. We aim to demonstrate how theoretically grounded views on the COVID-19 pandemic can help make psychological science stronger-not weaker-in its wake.

Performance and belief-based emotion regulation capacity and tendency: Mapping links with cognitive flexibility and perceived stress.

Cognitive reappraisal is among the most effective and well-studied emotion regulation strategies humans have at their disposal. Here, in 250 healthy adults across 2 preregistered studies, we examined whether reappraisal capacity (the ability to reappraise) and tendency (the propensity to reappraise) differentially relate to perceived stress. We also investigated whether cognitive flexibility, a skill thought to support reappraisal, accounted for associations between reappraisal capacity and tendency and perceived stress but found no evidence for this hypothesis. Both Studies 1 and 2 robustly showed that reappraisal tendency was associated with perceived stress, whereas a significant relationship between reappraisal capacity and perceived stress was only observed in Study 2. Further, Study 2 suggested that self-reported beliefs about one's emotion regulation capacity and tendency were predictive of wellbeing, whereas no such associations were observed with performance-based assessments of capacity and tendency. These data suggest that self-reported perceptions of reappraisal skills may be more predictive of wellbeing than actual reappraisal skills. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Visual and auditory brain areas share a representational structure that supports emotion perception.

Emotionally expressive music and dance occur together across the world. This may be because features shared across the senses are represented the same way even in different sensory brain areas, putting music and movement in directly comparable terms. These shared representations may arise from a general need to identify environmentally relevant combinations of sensory features, particularly those that communicate emotion. To test the hypothesis that visual and auditory brain areas share a representational structure, we created music and animation stimuli with crossmodally matched features expressing a range of emotions. Participants confirmed that each emotion corresponded to a set of features shared across music and movement. A subset of participants viewed both music and animation during brain scanning, revealing that representations in auditory and visual brain areas were similar to one another. This shared representation captured not only simple stimulus features but also combinations of features associated with emotion judgments. The posterior superior temporal cortex represented both music and movement using this same structure, suggesting supramodal abstraction of sensory content. Further exploratory analysis revealed that early visual cortex used this shared representational structure even when stimuli were presented auditorily. We propose that crossmodally shared representations support mutually reinforcing dynamics across auditory and visual brain areas, facilitating crossmodal comparison. These shared representations may help explain why emotions are so readily perceived and why some dynamic emotional expressions can generalize across cultural contexts.

Having more virtual interaction partners during COVID-19 physical distancing measures may benefit mental health.

Social interactions play an extremely important role in maintaining health and well-being. The COVID-19 pandemic and associated physical distancing measures, however, restricted the number of people one could physically interact with on a regular basis. A large percentage of social interactions moved online, resulting in reports of "Zoom fatigue," or exhaustion from virtual interactions. These reports focused on how online communication differs from in-person communication, but it is possible that when in-person interactions are restricted, virtual interactions may benefit mental health overall. In a survey conducted near the beginning of the COVID-19 pandemic (N2020 = 230), we found that having a greater number of virtual interaction partners was associated with better mental health. This relationship was statistically mediated by decreased loneliness and increased perceptions of social support. We replicated these findings during the pandemic 1 year later (N2021 = 256) and found that these effects held even after controlling for the amount of time people spent interacting online. Convergent with previous literature on social interactions, these findings suggest that virtual interactions may benefit overall mental health, particularly during physical distancing and other circumstances where opportunities to interact in-person with different people are limited.Open Science Framework repository: https://osf.io/6jsr2/ .

Computational methods in social neuroscience: recent advances, new tools and future directions.

Recent years have seen a surge of exciting developments in the computational tools available to social neuroscientists. This paper highlights and synthesizes recent advances that have been enabled by the application of such tools, as well as methodological innovations likely to be of interest and utility to social neuroscientists, but that have been concentrated in other sub-fields. Papers in this special issue are emphasized-many of which contain instructive materials (e.g. tutorials and code) for researchers new to the highlighted methods. These include approaches for modeling social decisions, characterizing multivariate neural response patterns at varying spatial scales, using decoded neurofeedback to draw causal links between specific neural response patterns and psychological and behavioral phenomena, examining time-varying patterns of connectivity between brain regions, and characterizing the social networks in which social thought and behavior unfold in everyday life. By combining computational methods for characterizing participants' rich social environments-at the levels of stimuli, paradigms and the webs of social relationships that surround people-with those for capturing the psychological processes that undergird social behavior and the wealth of information contained in neuroimaging datasets, social neuroscientists can gain new insights into how people create, understand and navigate their complex social worlds.

How does the brain navigate knowledge of social relations? Testing for shared neural mechanisms for shifting attention in space and social knowledge.

How does the human brain support reasoning about social relations (e.g., social status, friendships)? Converging theories suggest that navigating knowledge of social relations may co-opt neural circuitry with evolutionarily older functions (e.g., shifting attention in space). Here, we analyzed multivoxel response patterns of fMRI data to examine the neural mechanisms for shifting attention in knowledge of a social hierarchy. The "directions" in which participants mentally navigated social knowledge were encoded in multivoxel patterns in superior parietal cortex, which also encoded directions of attentional shifts in space. Exploratory analyses implicated additional regions of posterior parietal and occipital cortex in encoding analogous mental operations in space and social knowledge. However, cross-domain analyses suggested that attentional shifts in space and social knowledge are likely encoded in functionally independent response patterns. Additionally, cross-participant multivoxel pattern similarity analyses indicated that "directions'' of mental navigation in social knowledge are signaled consistently across participants and across different social hierarchies in a set of brain regions, including the right superior parietal lobule. Taken together, these results elucidate the neural basis of navigating abstract knowledge of social relations, and its connection to more basic mental operations.

Social network analysis for social neuroscientists.

Although social neuroscience is concerned with understanding how the brain interacts with its social environment, prevailing research in the field has primarily considered the human brain in isolation, deprived of its rich social context. Emerging work in social neuroscience that leverages tools from network analysis has begun to advance knowledge of how the human brain influences and is influenced by the structures of its social environment. In this paper, we provide an overview of key theory and methods in network analysis (especially for social systems) as an introduction for social neuroscientists who are interested in relating individual cognition to the structures of an individual's social environments. We also highlight some exciting new work as examples of how to productively use these tools to investigate questions of relevance to social neuroscientists. We include tutorials to help with practical implementations of the concepts that we discuss. We conclude by highlighting a broad range of exciting research opportunities for social neuroscientists who are interested in using network analysis to study social systems.

Similarity in functional brain connectivity at rest predicts interpersonal closeness in the social network of an entire village.

People often have the intuition that they are similar to their friends, yet evidence for homophily (being friends with similar others) based on self-reported personality is inconsistent. Functional connectomes-patterns of spontaneous synchronization across the brain-are stable within individuals and predict how people tend to think and behave. Thus, they may capture interindividual variability in latent traits that are particularly similar among friends but that might elude self-report. Here, we examined interpersonal similarity in functional connectivity at rest-that is, in the absence of external stimuli-and tested if functional connectome similarity is associated with proximity in a real-world social network. The social network of a remote village was reconstructed; a subset of residents underwent functional magnetic resonance imaging. Similarity in functional connectomes was positively related to social network proximity, particularly in the default mode network. Controlling for similarities in demographic and personality data (the Big Five personality traits) yielded similar results. Thus, functional connectomes may capture latent interpersonal similarities between friends that are not fully captured by commonly used demographic or personality measures. The localization of these results suggests how friends may be particularly similar to one another. Additionally, geographic proximity moderated the relationship between neural similarity and social network proximity, suggesting that such associations are particularly strong among people who live particularly close to one another. These findings suggest that social connectivity is reflected in signatures of brain functional connectivity, consistent with the common intuition that friends share similarities that go beyond, for example, demographic similarities.

How Does the Brain Infer Hidden Social Structures?

Many everyday thoughts and actions are shaped not only by our direct relationships with others, but also by our knowledge of relations between third-parties. Lau et al. recently demonstrated how knowledge of one type of social relation - interpersonal similarity - shapes cognition and behavior, and shed light on the neural basis of such phenomena.

Tools of the Trade Multivoxel pattern analysis in fMRI: a practical introduction for social and affective neuroscientists.

The family of neuroimaging analytical techniques known as multivoxel pattern analysis (MVPA) has dramatically increased in popularity over the past decade, particularly in social and affective neuroscience research using functional magnetic resonance imaging (fMRI). MVPA examines patterns of neural responses, rather than analyzing single voxel- or region-based values, as is customary in conventional univariate analyses. Here, we provide a practical introduction to MVPA and its most popular variants (namely, representational similarity analysis (RSA) and decoding analyses, such as classification using machine learning) for social and affective neuroscientists of all levels, particularly those new to such methods. We discuss how MVPA differs from traditional mass-univariate analyses, the benefits MVPA offers to social neuroscientists, experimental design and analysis considerations, step-by-step instructions for how to implement specific analyses in one's own dataset and issues that are currently facing research using MVPA methods.

Social network proximity predicts similar trajectories of psychological states: Evidence from multi-voxel spatiotemporal dynamics.

Homophily is a prevalent characteristic of human social networks: individuals tend to associate and bond with others who are similar to themselves with respect to physical traits and demographic attributes, such as age, gender, and ethnicity. Recent research using functional magnetic resonance imaging has demonstrated a positive relationship between individuals' real-world social network proximity (i.e., whether they are friends, friends-of-friends, or farther removed in social ties) and inter-subject correlation (ISC) in their time series of neural responses when viewing audiovisual movies. However, conventional ISC methods only capture information about similarity in the temporal evolution of region-averaged neural responses, and ignore information carried in fine-grained, spatially distributed response topographies. Here, we demonstrate that temporal trajectories of multi-voxel response patterns to naturalistic stimuli are exceptionally similar among friends and predictive of social network proximity, over and above the effects of response magnitude fluctuations. Furthermore, inter-subject similarity in the temporal trajectory of multi-voxel response patterns across distant points in time was particularly positively associated with individuals' proximity in their real-world social network. The fact that exceptional similarities among friends were most pronounced in long-range temporal fluctuations of response patterns located in multimodal cortical regions (e.g., regions of posterior parietal cortex) suggests that aspects of high-level processing during naturalistic stimulation may be particularly similar among friends. Given the localization of results, we speculate that socially close individuals may be particularly similar in endogenously driven shifts in how they distribute their attention (e.g., across the environment, within internal representations) over time. These results suggest that friends may experience exceptionally similar trajectories of psychological states when exposed to a common stimulus, and, more generally, that there are meaningful individual differences in the temporal evolution of multi-voxel response patterns during naturalistic stimulation.